Influence of vegetation structure, seasonality, and soil properties on rodent diversi community assemblages in west Mount Kilimanjaro, Tanzania

Abstract Rodent diversity and community assemblages are affected by several biotic and abiotic factors such as vegetation structure and seasonality. Vegetation structure particularly ground cover influences rodent diversity and community assemblages through provision of food resources and protection from predators. Such information is important for understanding species–habitat relationships for management and conservation. This study was conducted to determine the influence of vegetation structure, seasonality, and soil properties on species richness, abundance, community assemblages, and habitat association of rodents in west Mt Kilimanjaro. Rodent trapping was conducted using removal and capture–mark–recapture (CMR) methods with medium‐sized Sherman's live traps, snap, and Havarhart traps. Rodents were trapped during wet and dry seasons for three consecutive nights at 4 weeks intervals from April 2020 to March 2021. Environmental variables including vegetation structure, soil physical properties, and disturbance levels were recorded for each habitat type. Fourteen species of rodents were trapped in 25,956 trap nights. Rhabdomys pumilio, Praomys delectorum, and Lophuromys verhageni were the most dominant species across all habitats and seasons. L.verhageni occurred in all habitats while R.pumilio was restricted from occurring in montane forests. Moreover, species richness and abundance were influenced by habitat types, seasonality, soil type, and ground cover. Generally, both species richness and abundance were higher in fallows and montane forests and significantly lower in plantation forest and agricultural fields. In addition, rodent diversity was highest in fallows, followed by montane forests, and lowest in agricultural fields. Furthermore, rodents were associated with habitat types and vegetation structure forming two major community assemblages that significantly differed between habitats. Our study conclude that, community assemblages of rodents on Mt. Kilimanjaro were affected by functional spatial heterogeneity of the habitats occupied. Therefore, use of different habitats by rodents may be indicative of the landscape integrity and ecosystem changes based on species assemblages.


| INTRODUC TI ON
Rodents are among the most diverse and widely distributed mammals on earth. This is due to their ability to inhabit natural and seminatural habitats and consume almost everything (Kay & Hoekstra, 2008).They play a great role in ecological systems such as pollination and seed dispersal (Johnson et al., 2011). Rodents have low movement patterns and small home ranges (Saanya et al., 2021), which make them sensitive to changes in vegetation structure at smaller scales (Malcolm & Ray, 2000;Stirnemann et al., 2015); hence, they serve as ecological indicators of the environment (Avenant, 2003(Avenant, , 2011. The influence of habitat types, vegetation structure, and composition on rodent diversity and community assemblages is underlined by the habitat heterogeneity hypothesis (Stevens & Tello, 2011). The habitat heterogeneity hypothesis explains that heterogeneous habitats support high species diversity due to increased microhabitats that provide more niches for coexisting species (August, 1983;Stein & Kreft, 2015).
Heterogeneous habitats or habitat patches affect rodent diversity, abundance, and community assemblages through the provision of alternative microhabitats that serve as refuges and provide limiting resources to habitat generalists (Cramer & Willig, 2002;Mayamba et al., 2019Mayamba et al., , 2020Stein & Kreft, 2015). The influence of vegetation structure has been a central focus in the community ecology of small mammals including rodents (Cramer & Willig, 2002).
In addition, rodent diversity and community assemblage are influenced by many factors such as food availability, competition, predation, diseases and parasites, soil properties, climate, and altitude (Torre Corominas, 2004). For example, seasonal variations in rainfall distribution affect food quantity and quality which influences rodent's diet (Mulungu et al., 2011) and breeding patterns (Leirs et al., 1994(Leirs et al., , 1997Makundi et al., 2005Makundi et al., , 2007Mulungu et al., 2013). Physical properties of soil such as soil type/texture, bulk density and soil moisture influences the distribution, population size and survival of rodents due to burrowing for nests and cover Mlyashimbi et al., 2019). Furthermore, elevation range influences rodent species composition and distribution through vegetation zoning. Also, climate variability and anthropogenic activities in low altitudes affect vegetation zoning and rodent species distribution (Hemp, 2006;Lema & Magige, 2018;Mbugua, 2002).
Mount Kilimanjaro is the highest mountain in Africa (roof of Africa) and the world's famous heritage site and tourist attraction, with high diversity of rare and endemic small mammals including rodents (Grimshaw et al., 1995;Shore & Garbett, 1991;Verheyen et al., 2007). Despite that, research on community ecology of rodents on Mt Kilimanjaro has received relatively little scientific attention than high mountains of East and Central Africa, including Mount Elgon in Kenya and Uganda (Clausnitzer et al., 2003;Clausnitzer & Kityo, 2001), Mount Gecoche in Ethiopia (Bantihun & Bekele, 2015;Yihune & Bekele, 2012), and the Eastern Arc Mountains (Ademola et al., 2021;Chidodo et al., 2020;Makundi et al., 2007: Stanley et al., 1998Stanley & Hutterer, 2007). Most studies on these mountains including Mt Kilimanjaro have been focused on diversity and distribution of rodents along the altitudinal gradients. Previous studies along the Marangu, Mweka, and Shira routes of Mt. Kilimanjaro provided checklists and the distribution of rodent species in association with altitude (Grimshaw et al., 1995;Grimshaw & Foley, 1991;Mulungu et al., 2008;Stanley et al., 2014).
However, none of these studies investigated the influence of vegetation structure, seasonality, and soil properties on rodent community assemblages. Such knowledge is relevant to park managers for understanding species-habitat relationships for management and conservation purposes. Therefore, we aimed to determine the influence of vegetation structure, seasonality, and soil properties on rodent species richness and abundance in west Mt. Kilimanjaro.
Second, we aimed to determine community assemblages and habitat association of individual rodent species. We hypothesized that: (H1) Variations in vegetation structure, seasonality, and soil properties affect rodent species richness and abundance. We predict high rodent species richness and abundance in heterogeneous habitats.
Heterogeneous habitats have high primary productivity and ground cover which improves food availability and reduce predation risk (Cramer & Willig, 2002). (H2) Rodent community assemblage is influenced by structural complexity and heterogeneity of a habitat in association with other environmental variables. We predict that, community assemblage would vary remarkably across the habitats with respect to variations in vegetation structure and soil properties (Hernández et al., 2005). Moreover, heterogeneous habitats of Mt Kilimanjaro would support higher diversity and strong interactions of rodent communities due to complex ecosystems as compared with simple habitats .

K E Y W O R D S
community assemblage, Mount Kilimanjaro, rodent diversity, vegetation structure

T A X O N O M Y C L A S S I F I C A T I O N
Community ecology 2 | MATERIAL AND ME THODS

| Study site description
The study was conducted on Mount Kilimanjaro which is located in northeastern Tanzania. The study area lies between 3°07S and 37°35E on the western slopes of Mt Kilimanjaro in Siha district, covering a total area of 1668 km 2 and reaching a maximum altitude of 5895 m a.s.l. (Figure 1). According to Mulangu and Kraybill (2013) the Mountain is characterized by a tropical montane climate with two rainy and two dry seasons. Rainy season 1 is a long and major season from March to May, and rainy season 2 is a short and minor one from October to December. Also, there is dry season 1 which is the shortest and driest one from January to February, as well as dry season 2 which is long and less dry from June to September. Frosts are also common from June to August during the nights (Thompson et al., 2002). The estimated mean annual rainfall ranges from 700 mm in the lowlands to around 2200 mm in highlands. The general range of temperatures is between −6°C in the highlands and 29°C in the lowlands. The parent material for most soils in the area is volcanic ash and pumice which are typically well-drained. The soils are highly fertile and predominantly dark grayish, dark brown, and dark yellowish-brown with sandy and clay loams (Nanzyo et al., 1993).
Generally, the mountain is covered with a zonation of habitat types along the altitudinal gradient (Hemp, 2006;Mulungu et al., 2008). Habitat types were classified as plantation forest and cultivated zone, montane rain forest, alpine heath, and moorland. Plantation forest and cultivated zones range from 1500 to 2400 m a.s.l. covering a total area of 7630 ha. It occupies a transition zone between human settlements with an estimated human population of 2500 people (Mbonile et al., 2003;National Bureau of Statistics, 2012 (Hemp, 2006). Protea kilimandscharica, Kniphofia thomsonii, and Lobelia deckenii are also prevalent. It is the coldest with day and night temperatures ranging from 10 to 21 and −1 to 10°C respectively.

| Study design and sampling procedures
The study was purposively conducted in seven habitat types: agricultural fields AGR, fallows FLW, plantation forest PLF, lower DSF and higher MFR montane forests, ecotone/alpine heath ECT, and moorland MLD between April 2020 and March 2021. To maximize capture and diversity of rodents two methods, capture-markrecapture/release (CMR) and removal techniques were employed for rodent trapping with a combination of different traps as conducted by Welegerima et al. (2020) and Shilereyo et al. (2020).
In capture-mark-recapture (CMR) method, permanent experimental grids of 70 m × 70 m (with a 10 m buffer from the edges) were established in both fallows, higher montane forest, and moorland.
Two replicate grids at a minimum distance of 500 m were established in each of the fallow and moorland habitats and three replicate grids in higher montane forest, making a total of seven grids. For each grid, medium-sized Sherman's live traps (23 × 9.5 × 8 cm H.B. Sherman's Traps, Inc.) were arranged in seven lines with seven trapping stations 10 m apart making a total of 49 traps. Traps were baited with peanut butter mixed with maize flour and left for three consecutive nights. Trapping was conducted every month at a 4-week interval.
Traps were inspected every morning before 10:00 am to avoid death and suffocation from harsh weather conditions. Trapped individuals were toe clipped and coded following animal health and safety marking procedures (Borremans et al., 2015). Animals were weighed, sexed, and their reproductive conditions examined. Finally, trapped animals were released at a capture station, and the traps were rebaited for the next trapping night.
In the removal method, trapping was conducted in all seven habitat types using a combination of traps following procedures described in Shilereyo et al. (2020) and Welegerima et al. (2020). For each habitat type, at least four plots were randomly selected. Five transect lines 50 m long and 10 m apart were established in each plot. Sherman and snap traps (1.0 × 8.5 × 16.5 cm) were alternately placed in 10 trapping stations spaced 5 m apart. In addition, four wire cages/Havahart traps (60 × 15 × 170 cm) were randomly placed in the plot specifically for trapping larger species such as Cricetomys and squirrels (Shilereyo et al., 2020;Welegerima et al., 2020

| Habitat characterization
In each of the seven habitats, two main sample plots each measuring 50 m × 20 m were established on the existing plots/grids used for rodent trapping resulting in a total of 14 plots. A nested quadrant approach which is a modified Whittaker method was employed as narrated by Stohlgren et al. (1995). The plots were used for recording trees encountered within and identified to species level. Tree diameter at breast height (DBH) was measured using a caliper, and were identified and enumerated. Percentage cover was used as an indirect measure of the performance of the species found within the plot using a scale of 0%-100%. Therefore, a single species covering the entire plot was given a score of 100%. Ground cover was estimated as the total percentage cover of grasses in proportion to bare soil using a scale of 0%-100%. Canopy cover was estimated as the percent of a forest area occupied by the vertical projections of tree crowns following procedures described by Avsar and Ayyildiz (2010). In addition, soil composite samples (250 g) and soil cores at 30 cm depth were collected and preserved in zipper bags for laboratory analysis of soil physical properties such as soil type, pH, bulk density, and soil moisture (Gee & Bauder, 1986).
Disturbance levels were assigned subject to observations in the field and were ranged from 1 to 3. Disturbance levels were based on the presence-absence of human activities such as logging, cultivation, and entrepreneurial facilities (restaurants). History of fire occurrences and disturbance from wild animals were also used. In addition, disturbance levels were based on location of the habitat whether inside or outside the park. For example, agricultural fields and plantation forests were assigned disturbance level 3 (highly disturbed) because they were located outside the national park and were predominated by human activities. Lower montane forest and fallow were assigned disturbance level 2 (moderately disturbed) because they had minimal human intervention despite of being located outside the park. Higher montane forest, ecotone, and moorland were located inside the national park hence were assigned disturbance level 1 (less disturbed only by wild animals).

| Data analysis
Trapped animals from both the CMR and removal methods were combined. However, to standardize the sample size, recaptured individuals in the CMR method were not considered for estimating rodent abundance. Following methods by Chidodo et al. (2020), Shilereyo et al. (2020)  and Pi denotes the proportion of individuals found in the ith species (Shannon & Weaver, 1949). Chi-square test χ 2 was used to compare the variation in rodent species composition across habitats and seasons. However, following a modified technique by Chidodo et al. (2020), three species such as Arvicanthis niloticus, Pelomys fallax, and Aethomys kaiseri were excluded from the analysis due to their low representation (Table 1). In addition to that, soil samples were processed and analyzed in the laboratory following procedures explained in Gee and Bauder (1986) and FAO (2006).
Pearson's pairwise correlation analysis in R was conducted for multicollinearity of the independent variables at r ≥ .5 (Appendix A).
Correlated variables were excluded from the same model (Smith & Warren, 2019). Before statistical analyses, assumptions of general linear models such as normality (using Shapiro test and Q-Q plots), independence of variance, and heterogeneity were checked (Smith & Warren, 2019;Zuur & Ieno, 2016). Unlike the data for species richness, rodent abundance did not follow the normal distribution and the data were over dispersed. Due to that, negative binomial distribution models (with log link function) were fitted for rodent abundance. We ran different models in which rodent species richness and abundance were allowed to differ between habitat types, seasonality, and soil types. Also, they were allowed to vary with ground cover, herbs density, soil bulk density, and the interactions between them (Appendix B and C). Akaike information criterion (AIC) was used for model selection whereby the one with the lowest AIC was selected as best model that better describe our data (Burnham & Anderson, 2004). An F-test was used for goodness of fit of the model and R 2 for the explained variation in rodent species richness. Moreover, two-way anova (p ≤ .05) was used to compare estimates of rodent abundance and species richness across habitats and seasons.
For community assemblages and habitat association of rodents, cluster analysis of rodent samples was performed in the PRIMER v6 program (Clarke & Warwick, 2001). Bray-Curtis similarity matrix with a distance measure was used to cluster the samples (Bray & Curtis, 1957). Previously, the data were square-root transformed to reduce the influence of dominant species (Clarke & Warwick, 2001).
The similarity profile test (SIMPROF) was performed to determine genuine clustering and structuring of rodent samples and statistically test the difference between and within the clusters (Clarke & Warwick, 2001). Analysis of similarity (ANOSIM) test was performed for similarity of rodent community assemblages or clusters between pairs of habitats. Analysis was based on 999 times permutations with the sample statistic Global R (0-1) and the significance level of sample statistic (pi) p ≤ .05 (Clarke & Warwick, 2001). Furthermore, canonical correspondence analysis (CCA) was performed in PAST Paleontological Statistics software (Hammer et al., 2002) at the correlation coefficient (r ≥ .5). An ordination plot showing the association between individual species and habitat attributes was produced (Hammer et al., 2002;McCune et al., 2002).

| Community assemblages and habitat association
From cluster analysis based on the Bray-Curtis dissimilarity index, there was evidence of genuine structuring of rodent samples forming two major community assemblages/clusters at 99% efficiency ( Figure 2). Community assemblage one (C1) predominated in forested habitats mainly in ecotone, montane (higher and lower), and plantation forests. Whereas, the second community assemblage (C2) predominated in the moorland, fallow, and agricultural fields ( Figure 2). The SIMPROF test showed a statistically significant difference between and within the two clusters with sample statistic (pi) of 2.483, p = .002 at 999 permutations. Furthermore, the ANOSIM test showed statistically significant differences in community assemblages between pairs of habitats at sample statistic (Global R) = .05, p = .01 at 999 permutations (Table 6). For example, agricultural fields AGR were completely distant and significantly different from both lower DSF and higher MFR montane forests (Global-R statistic = 1, p = .029) and not significantly different from fallow FLW (Global-R statistic = .218, p = .119). Moorland MLD was significantly different from both lower and higher montane forests (Global-R statistic = .833, p = .005) ( Table 6).
In addition, CCA canonical correspondence analysis explained about 80% of the variations in two axes (Figure 3 Indicating that, Dendromus was more associated with shrub density and soil moisture and their abundance increased with increasing shrub density. Whereas, M. natalensis was more associated with agricultural fields and disturbance (Figure 3).

| Species composition, community assemblages, and habitat association
Results indicated that, 14 species of rodents were recorded across habitats and seasons. Out of the captured species, two major F I G U R E 2 Dendrogram based on Bray-Curtis similarity distance measure showing two broad clusters of rodent communities among the rodent samples across the study area. There was a significant structuring between and within the two major clusters (community assemblages). AGR1-4, PLF 1-4, FLW 1-6, MLD 1-6, ECT 1-4, MFR1-4 and DSF 1-4 refers to replicated sites in agricultural fields, plantation forest, fallow, moorland, ecotone, higher montane forest, and lower montane forest, respectively. Note: There were significant differences in rodent community assemblages between pairs of habitats. Sample statistic (global R) = .5, significance level statistic p = .001.

TA B L E 6
Results from analysis of similarity test ANOSIM on rodent community assemblages at 999 permutations community assemblages with different composition were formed. with sparse vegetation favoring opportunistic species. It is reported that community assemblage of rodents is determined by the coexistence of species which depends on species-specific traits such as nesting, food availability, and predation risk (Cramer & Willig, 2002).
Consistently, in this study, rodents were associated not only with distinct habitat types but also with vegetation attributes. For example, in community assemblage one, Praomys delectorum and Graphiurus murinus were more dominant in montane forests than in plantation forest. The species were positively associated with tree and herb density, leaf litter, and canopy cover probably because they are habitat specialists and typical forest-adapted species that prefer areas with dense canopy and vegetation cover. Dense herbs and leaf litter provide enough food, protection from predators, and nesting grounds for the species. Canopy cover maintains humidity and soil moisture which creates suitable microclimate for P. delectorum (Bantihun & Bekele, 2015). Similarly, P. delectorum has been reported a closed forest dweller that forages on deep leaf litter (Happold, 2013) and builds its nest from litter and other vegetative materials (Monadjem et al., 2015). Moreover, P. delectorum has been previously reported as the dominant species in montane forests of Mt Kilimanjaro Stanley et al., 2014), Mt Elgon in Kenya and Uganda  and other mountains including the Eastern Arc Mountains (Ademola et al., 2021;Chidodo et al., 2020;Makundi et al., 2007;Stanley et al., 1998). In addition, P. delectorum is reported to inhabit both intact and disturbed forests (Ademola et al., 2021;Gitonga et al., 2016;Monadjem et al., 2015;Mulungu et al., 2008) as well as edges between forest and ecotone . On the contrary, low percentage composition of P. delectorum in plantation forest (despite it is a forest-adapted species) was probably due to high levels of disturbance from anthropogenic activities including cultivation, logging, and firewood collection. These activities result into habitat destruction and fragmentation which adversely affects the survival of native species.
Rhabdomys pumilio, L. verhageni, M. natalensis, and Dendromus spp were the most abundant species in the second community assemblage. R. pumilio predominated in the moorland and agricultural fields and was moderately associated with ground cover, probably because it is most important and preferred food is grass and seeds hence commonly named the grass rat Shore & Garbett, 1991;Happold, 2013 harsh during the night) by being active during the day. In contrast, Grimshaw et al. (1995) and Stanley et al. (2014) (Verheyen et al., 2007). It occurred across all habitats and seasons hence termed a habitat generalist. Similarly, species of the same genus have been reported to occur in moist places of montane forests (from 500 m s.a.l in lowland forests) and highland habitats up to 4500 m a.s.l in the Afro-alpine zone (Bantihun & Bekele, 2015;Happold, 2013). They are widely distributed in bushlands, fallows, plantation forests, montane forests, heath lands, and alpine zones in East, Central, and South Africa (Bantihun & Bekele, 2015;Clausnitzer et al., , 2003Happold, 2013;Mulungu et al., 2008;Ssuuna et al., 2020;Stanley et al., 1998Stanley et al., , 2014Stanley & Kihaule, 2016).  (Mulungu et al., , 2014Mulungu, 2017). As a habitat generalist and opportunist, M. natalensis takes advantage of human disturbance due to the available food resources from cultivation (Happold, 2013;Lema & Magige, 2018;Mulungu et al., 2013Mulungu et al., , 2014.
Dendromus spp were associated with fallow and moorland habitats and positively correlated with shrub density and soil moisture.
More individuals of Dendromus spp were trapped in dense patches of Erica bushes. Similarly, Happold (2013) reported that Dendromus spp is among the species occurring in high abundance above the tree line preferably in dense shrubs and moist places. On the contrary, species such as Aethomys kaiseri, Arvicanthis niloticus, and Pelomys fallax were underrepresented across both habitats and seasons. This observation could be attributed to trapping in higher altitudes from 1500 a m.s.l and above while the species are said to be widely distributed in low-elevation grasslands and bushes (Grimshaw et al., 1995;Stanley et al., 1998).
Generally, most of the trapped species in this study have been previously captured on both sides of Mt. Kilimanjaro and their distribution and conservation status are well known (Grimshaw et al., 1995;Mulungu et al., 2008;Stanley et al., 2014). However, Pelomys fallax has never been previously reported along the Shira route, and therefore, its distribution and conservation status is poorly known. The smaller number of individuals trapped in the current study (n = 5) is consistent with Happold (2013) Mulungu et al. (2008) and Stanley et al. (2014) in the same study area. This was probably because our study had an extensive sampling period throughout the year covering a relatively large area with a combination of methods and traps.

| Influence of vegetation structure, seasonality, and soil type on species richness and abundance
Fallow was the most diverse habitat probably due to high ground cover and shrub density which provide niches for many species (Cramer & Willig, 2002). Fallows are intermediates between agricultural fields and montane forests that serve as refuge to other rodents providing alternative food resources and protection from predators (Cramer & Willig, 2002;Makundi et al., 2010). Montane forests (both higher MFR and lower DSF) were the next diverse habitats with high rodent species richness and abundance. This was probably due to high canopy and ground cover, high vegetation density, and plant species diversity (particularly in the higher montane) forest which provides food and protection to rodents. Lower montane forest on the other hand, had high species diversity and abundance despite the fact that it was less dense than higher montane forest. This was due to moderate disturbance which provided microhabitats to habitat generalists such as L. verhegeni, G. dolichurus and Mus musculoides (Ademola et al., 2021;Mulungu et al., 2008). Similarly, a study by Mulungu et al. (2008) reported maximum rodent abundance in montane forests that decreased above the tree line forming a hump-shaped distribution, due to maximum rainfall at mid-elevation (Hemp, 2006). Montane forests receive maximum amount of rainfall which increases primary productivity hence improves vegetation structure and food availability (Clausnitzer & Kityo, 2001). Similar patterns of rodent abundance in montane forests have been reported in the Mabira central forest reserve in Uganda and the Ukaguru Mountains of Tanzania (Ademola et al., 2021;Ssuuna et al., 2020). On the contrary, agricultural fields, plantation forest, and moorland were the least diverse among the seven habitats with lower species richness and abundance. This observation was linked to high disturbance from anthropogenic activities in the agricultural fields and plantation forest which affect the integrity of habitats and reduce diversity of most rodents (Bennett, 1990). In addition, poor vegetation structure and adverse environmental conditions in the moorland affect the survival and distribution of Afro-alpine rodents . Afro alpine environments are characterized by extreme cold weather which restricts movement and activity pattern of rodents forcing them to take cover inside burrows and grasses.
In addition to habitat type and ground cover, seasonality influenced rodent species richness and abundance. However, the influence of seasonality on rodent species richness was not significant probably because most species occurred across both dry and wet seasons. Rodent abundance was relatively higher in the dry season than in wet season. This was probably due to that most species start breeding 1 month after the long rains until the end of wet season.
During this period, there is high cover and green foliage which triggers breeding in most rodents (Mlyashimbi et al., 2018). Therefore, rodent population tends to peak 2-4 months later . Similarly, it is reported that the variation in rainfall distribution influence rodents' diet (Mulungu et al., 2011) and breeding patterns (Leirs et al., 1994;Mlyashimbi et al., 2018;Mulungu et al., 2014) through resource availability which in turn affect population abundance (Leirs et al., 1997;Makundi et al., 2007). Moreover, the observed high abundance in dry season could be a result of crop remains in agricultural fields which ensures continuous food supply to rodents inhabiting them.
Furthermore, soil type and microclimate have been reported to influence the distribution, population abundance, and survival of rodents elsewhere Meliyo et al., 2014;Mlyashimbi et al., 2019). In this study, clay soil had higher rodent species richness and abundance than other soils probably because of its good texture. Clay soil hardens during the rainy season allowing the survival of rodents (Meliyo et al., 2014). While other volcanic ash soils of Mt. Kilimanjaro have low bulk density and poor structure that can easily collapse or shrink during rainy season making them unsuitable for most rodents (Nanzyo et al., 1993). However, our re-

| CONCLUSION AND RECOMMENDATION
Results from this study indicated that rodent species richness and abundance in west Mt. Kilimanjaro were a result of several factors including habitat types in synergy with vegetation structure, seasonality, and soil physical properties. Rodent community assemblages reflected the variation in habitat types, vegetation structure, and disturbance level along the altitudinal gradient.
Moreover, Mt. Kilimanjaro has heterogeneous habitats that support high diversity of rodents with fallows and montane forests being the most diverse habitats supporting complex communities.

ACK N OWLED G M ENTS
We would like to convene our sincere gratitude to the African University of Agriculture SUA for assisting in rodent community analysis using PRIMER v6 program.

CO N FLI C T O F I NTE R E S T
Authors declare no conflict of interest among themselves.

DATA AVA I L A B I L I T Y S TAT E M E N T
Authors agree to deposit the data associated with this study in an